When implementing a quantized GEMM/convolution with INT8 activations and weights, it's common to also have the bias as INT32. The usual trick for adding a bias seems to be initializing the C matrix to ...

This paper presents an open-source library that pushes the limits of performance portability for irregular General Matrix Multiplication (GEMM) on the widely-used Arm architectures. Our library, ...

When compiling the sample code for examples/16_ampere_tensorop_conv2dfprop/ampere_tensorop_conv2dfprop.cu, it fails with the following error message. Any other ...

A technical paper titled “Efficient Approaches for GEMM Acceleration on Leading AI-Optimized FPGAs” was published by researchers at The University of Texas at Austin and Arizona State University.

Abstract: Systolic array architectures have recently emerged as successful accelerators for deep convolutional neural network (CNN) inference. Such architectures can be used to efficiently execute ...

Abstract: Neural networks have been used for a long time for image detection and recognition applications due to their ability and efficiency in complex problem solving. Several researchers have ...